Abstract
Home-based online learning is a typical application of personal learning environment. Understanding the adaptability and characteristics of college students in the personal learning environment (PLE) can effectively tap the potential of online courses and provide valuable references for learners' online and lifelong learning. In this single-group study, 80 college students received a 90-min self-regulated learning training. In pre- and post-class evaluations, media multi-tasking self-efficacy, perceived attention problems, self-regulation strategies and learning satisfaction are used as key variables in online learning to assess their personal learning environment adaptability and characteristics. Using descriptive statistics and one-dimensional intra-group variance to analyze the data, it was found that: Learners have a moderate degree of attention deficit in their personal learning environment, which is manifested in three aspects: perceived attention discontinuity, lingering thought, social media notification.; Under simple training or natural conditions, students have poor adaptability in the personal learning environment, and their behavior perception and behavior adjustment levels have improved, but they have not yet reached expectations; Participation in online learning has significantly increased the application of learners' self-regulation strategies, especially the application of behavior strategies.
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Acknowledgements
This work is funded by the National Natural Science Foundation of China [Grant No. 62077017, Grant No. 62007020], Shandong Social Science Planning Project of China [Grant No. 18DJYJ07] and Shandong Province Higher Educational Research Program of China [Grant No. J18RA144].
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Chen, C., Meng, X., Liu, J., Liu, Z. (2021). Do College Students Adapt to Personal Learning Environment (PLE)? A Single-Group Study. In: Deze, Z., Huang, H., Hou, R., Rho, S., Chilamkurti, N. (eds) Big Data Technologies and Applications. BDTA WiCON 2020 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 371. Springer, Cham. https://doi.org/10.1007/978-3-030-72802-1_3
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